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| Title: | Adaptive critic based neurocontroller for autolanding of aircrafts | |
| Author (s): | Balakrishnan, S. N. Saini, G. | |
| Department/Lab Affiliations: | Mechanical & Aerospace Engineering | |
| Keywords: | Hamiltonian equations PID controller adaptive control adaptive critic based neural networks aircraft autolanding aircraft landing guidance autopilot closed loop optimal control control system synthesis elevator deflection flare mode glideslope mode longitudinal dynamics neurocontroller neurocontrollers wind disturbances wind gusts | |
| Issue Date: | 1997 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Saini, G.; Balakrishnan, S. N. "Adaptive critic based neurocontroller for autolanding of aircrafts" American Proceedings of the 1997 Control Conference, 1997. Vol.2, 4-6 Jun 1997 Pages:1081-1085 vol.2 | |
| Abstract: | In this paper, adaptive critic based neural networks have been used to design a controller for a benchmark problem in aircraft autolanding. The adaptive critic control methodology comprises successive adaptations of two neural networks, namely action and critic network (which approximate the Hamiltonian equations associated with optimal control theory) until closed loop optimal control is achieved. The autolanding problem deals with longitudinal dynamics of an aircraft which is to be landed in a specified touchdown region (within acceptable ranges of speed, pitch angle and sink rate) in the presence of wind disturbances and gusts using elevator deflection as the control for glideslope and flare modes. The performance of the neurocontroller is compared to that of a conventional proportional-integral-differential (PID) controller. The results show that the neurocontrollers have good potential for aircraft applications | |
| Type: | Article - Conference proceedings text | |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: | |
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| title | Adaptive critic based neurocontroller for autolanding of aircrafts | |
| contributor.author | Balakrishnan, S. N. | |
| contributor.author | Saini, G. | |
| contributor.deptlab | Mechanical & Aerospace Engineering | |
| subject | Hamiltonian equations | |
| subject | PID controller | |
| subject | adaptive control | |
| subject | adaptive critic based neural networks | |
| subject | aircraft autolanding | |
| subject | aircraft landing guidance | |
| subject | autopilot | |
| subject | closed loop optimal control | |
| subject | control system synthesis | |
| subject | elevator deflection | |
| subject | flare mode | |
| subject | glideslope mode | |
| subject | longitudinal dynamics | |
| subject | neurocontroller | |
| subject | neurocontrollers | |
| subject | wind disturbances | |
| subject | wind gusts | |
| date.issued | 1997 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Saini, G.; Balakrishnan, S. N. "Adaptive critic based neurocontroller for autolanding of aircrafts" American Proceedings of the 1997 Control Conference, 1997. Vol.2, 4-6 Jun 1997 Pages:1081-1085 vol.2 | |
| identifier.pub.URI | ||
| description.abstract | In this paper, adaptive critic based neural networks have been used to design a controller for a benchmark problem in aircraft autolanding. The adaptive critic control methodology comprises successive adaptations of two neural networks, namely action and critic network (which approximate the Hamiltonian equations associated with optimal control theory) until closed loop optimal control is achieved. The autolanding problem deals with longitudinal dynamics of an aircraft which is to be landed in a specified touchdown region (within acceptable ranges of speed, pitch angle and sink rate) in the presence of wind disturbances and gusts using elevator deflection as the control for glideslope and flare modes. The performance of the neurocontroller is compared to that of a conventional proportional-integral-differential (PID) controller. The results show that the neurocontrollers have good potential for aircraft applications | |
| type | Article - Conference proceedings | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| rights.URI | ||
| date.accessioned | 2007-04-05T14:02:24Z | |
| date.available | 2007-04-05T14:02:23Z | |
| identifier.persist.URI | ||
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